Demographics for all included participants.
| Demographics | ||||
| Summary | ||||
| N | Age (years) | Education (years) | Sex (M/F/O) | EHI |
|---|---|---|---|---|
| 844 | 29.08 (6.03) | 14.38 (2.48) | 441/391/12 | 5.09 (79.37) |
| Race | n |
|---|---|
| White | 606 |
| Black or African American | 82 |
| Multiple | 76 |
| Asian | 69 |
| American Indian or Alaska Native | 5 |
| Native Hawaiian or Other Pacific Islander | 3 |
| Other | 3 |
| Hispanic ethnicity | n |
|---|---|
| No | 744 |
| Yes | 100 |
Demographics for included participants, by handedness group (EHI bins).
| Handedness | N | Age (years) | Education (years) | Sex (M/F/O) | EHI |
|---|---|---|---|---|---|
| Left | 331 | 28.84 (6.1) | 14.45 (2.39) | 170/157/4 | -81.61 (19.27) |
| Mixed | 135 | 28.83 (6.17) | 14.58 (2.6) | 77/56/2 | -8.89 (26.49) |
| Right | 378 | 29.38 (5.93) | 14.24 (2.5) | 194/178/6 | 86.01 (16.61) |
| Left: (EHI <= -40) | Mixed: (-40 < EHI < 40) | Right: (EHI >= 40) | |||||
Do we find an interaction of field x level x handedness, when
handedness is binned as left (EHI <= -40) or right (EHI > +40)?
Summary. For reaction time, we find
the critical interaction in the predicted direction (11.67ms, 95%CI
[0.65, 22.69], p = .019, one-sided). Accuracy stats are in progress: the
interaction effect will be close to zero, opposite the predicted
direction (the point estimates are 1.76 for righties and 1.96 for
lefties).
Error bars show 95% CI.
Reaction time is modeled as a linear effect of field, level, and
handedness, using data from every target-present trial with a “go”
response:
lmer( rt ~ field*level*handedness + (1 | subject) )
| Field by level by handedness interaction (RT) | |||||||
| ANOVA: compare models with vs. without interaction term | |||||||
| npar | AIC | BIC | logLik | deviance | Chisq | Df | p.value1 |
|---|---|---|---|---|---|---|---|
| 9 | 1,166,282.858 | 1,166,367.139 | −583,132.429 | 1,166,264.858 | - | - | - |
| 10 | 1,166,280.551 | 1,166,374.197 | −583,130.276 | 1,166,260.551 | 4.307 | 1 | .038 |
| 1 F-test (two-sided? https://daniellakens.blogspot.com/2016/04/one-sided-f-tests-and-halving-p-values.html) | |||||||
| Field by level by handedness interaction (RT) | |||||||||
| Compare effect estimate to zero with emmeans() | |||||||||
| field_consec | level_consec | handedness_consec | estimate1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|---|
| LVF - RVF | Local - Global | Right - Left | 11.666 | 5.622 | Inf | 0.648 | 22.685 | 2.075 | .038 |
| 1 A positive number means LVF global bias is stronger in right handers (as predicted by AAH) | |||||||||
| 2 Z-approximation | |||||||||
| 3 Confidence level: 95% | |||||||||
| 4 Two-sided | |||||||||
| LVF Global bias by handedness bin (RT) | |||||||||
| field_consec | level_consec | handedness | estimate1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|---|
| LVF - RVF | Local - Global | Left | 15.641 | 4.096 | Inf | 7.613 | 23.669 | 3.819 | .0001 |
| LVF - RVF | Local - Global | Mixed | 21.658 | 6.414 | Inf | 9.087 | 34.228 | 3.377 | .0007 |
| LVF - RVF | Local - Global | Right | 27.307 | 3.829 | Inf | 19.802 | 34.812 | 7.131 | <.0001 |
| 1 A positive number means global bias (faster RT for global) | |||||||||
| 2 Z-approximation | |||||||||
| 3 Confidence level: 95% | |||||||||
| 4 Two-sided, uncorrected | |||||||||
| Field by level interaction (RT) | |||||
| Old-school Omnibus F-test | |||||
| term | df | sumsq | meansq | statistic | p.value |
|---|---|---|---|---|---|
| field | 1 | 1,664,691.722 | 1,664,691.722 | 23.612 | <.0001 |
| level | 1 | 9,626,122.373 | 9,626,122.373 | 136.54 | <.0001 |
| handedness | 1 | 10,185,712.46 | 10,185,712.46 | 144.477 | <.0001 |
| field:level | 1 | 2,730,949.837 | 2,730,949.837 | 38.737 | <.0001 |
| field:handedness | 1 | 1,505,316.949 | 1,505,316.949 | 21.352 | <.0001 |
| level:handedness | 1 | 12,247.994 | 12,247.994 | 0.174 | .677 |
| field:level:handedness | 1 | 127,954.685 | 127,954.685 | 1.815 | .178 |
| Residuals | 86,205 | 6,077,502,195.866 | 70,500.576 | - | - |
Error bars show 95% CI.
In progress.
Accuracy is modeled as a binomial effect of field, level, and
handedness, using binary correct/incorrect data from every
target-present trial:
glmer( correct ~ field*level*handedness + (1 | subject), family = "binomial" )
| Field by level by handedness interaction (Accuracy) | |||||||
| ANOVA: compare models with vs. without interaction term | |||||||
| npar | AIC | BIC | logLik | deviance | Chisq | Df | p.value1 |
|---|---|---|---|---|---|---|---|
| 8 | 32,836.316 | 32,911.643 | −16,410.158 | 32,820.316 | - | - | - |
| 9 | 32,837.667 | 32,922.41 | −16,409.833 | 32,819.667 | 0.65 | 1 | .42 |
| 1 F-test (two-sided? https://daniellakens.blogspot.com/2016/04/one-sided-f-tests-and-halving-p-values.html) | |||||||
| Field by level by handedness interaction (Accuracy) | ||||||||||
| Compare effect estimate to zero with emmeans() | ||||||||||
| field_consec | level_consec | handedness_consec | odds.ratio1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | null | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|---|---|
| LVF / RVF | Local / Global | Right / Left | 1.113 | 0.145 | Inf | 0.862 | 1.436 | 1 | 0.82 | .412 |
| 1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias is stronger in the LVF for right handers (predicted by AAH) | ||||||||||
| 2 'Inf' df is expected when emmeans does logistic regression. See emmeans FAQ: https://cran.r-project.org/web/packages/emmeans/vignettes/FAQs.html#asymp. | ||||||||||
| 3 Confidence level: 95% | ||||||||||
| 4 Two-sided | ||||||||||
| LVF Global bias by handedness bin (Accuracy) | ||||||||||
| Compare effect estimate to zero with emmeans() | ||||||||||
| field_consec | level_consec | handedness | odds.ratio1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | null | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|---|---|
| LVF / RVF | Local / Global | Left | 0.503 | 0.048 | Inf | 0.417 | 0.607 | 1 | −7.193 | <.0001 |
| LVF / RVF | Local / Global | Mixed | 0.916 | 0.136 | Inf | 0.685 | 1.225 | 1 | −0.591 | .554 |
| LVF / RVF | Local / Global | Right | 0.571 | 0.05 | Inf | 0.481 | 0.677 | 1 | −6.414 | <.0001 |
| 1 Backtransformed to odds ratio from log odds ratio (tests are performed on log odds ratio scale). A ratio > 1 means global bias is stronger in the LVF, as predicted for right handers. Mixed handers' global bias is shown here, but their data was not included in the binomial model. | ||||||||||
| 2 'Inf' df is expected when emmeans does logistic regression. See emmeans FAQ: https://cran.r-project.org/web/packages/emmeans/vignettes/FAQs.html#asymp. | ||||||||||
| 3 Confidence level: 95% | ||||||||||
| 4 Two-sided | ||||||||||
Do we find an interaction of field x level x handedness (continuous EHI score)?
Summary. For reaction time, we find the critical interaction in the predicted direction (.067ms per EHI unit, 95% CI [0.003, 0.13], p = .020, one-sided). This slope corresponds to 14.82ms for EHI = -100, and 28.14ms for EHI = +100. Accuracy stats are in progress.
Model RT as a linear effect of field, level, and EHI (continuous):
rt_model_ehi <- lmer( rt ~ field*level*ehi + (1 | subject) )
| Field by level by ehi interaction (RT) | |||||||
| ANOVA: compare models with vs. without interaction term | |||||||
| npar | AIC | BIC | logLik | deviance | Chisq | Df | p.value1 |
|---|---|---|---|---|---|---|---|
| 9 | 1,387,640.958 | 1,387,726.807 | −693,811.479 | 1,387,622.958 | - | - | - |
| 10 | 1,387,638.71 | 1,387,734.097 | −693,809.355 | 1,387,618.71 | 4.248 | 1 | .039 |
| 1 F-test (two-sided? https://daniellakens.blogspot.com/2016/04/one-sided-f-tests-and-halving-p-values.html) | |||||||
| Field by level interaction (RT) | ||||||||
| Compare effect estimate to zero with emmeans() | ||||||||
| field_consec | level_consec | estimate1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|
| RVF - LVF | Global - Local | 0.067 | 0.032 | Inf | 0.003 | 0.13 | 2.061 | .039 |
| 1 A positive number means global bias is stronger in LVF for right handers (as predicted), in ms per EHI unit (-100 to 100). Multiply this value by 200 to get the estimated difference in LVF global bias for strong left vs. right handers. | ||||||||
| 2 Z-approximation | ||||||||
| 3 Confidence level: 95%. Lower CI for one-sided test: 0.013. | ||||||||
| 4 Two-sided | ||||||||
| Field by level interaction (RT) | |||||||
| Compare effect estimate to zero with emmeans() | |||||||
| contrast | estimate1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|
| LVF Local - LVF Global | 0.033 | 0.023 | Inf | −0.025 | 0.092 | 1.459 | .463 |
| RVF Local - RVF Global | −0.033 | 0.023 | Inf | −0.092 | 0.026 | −1.454 | .465 |
| 1 A positive number means more global bias for right handers, in ms per EHI unit (-100 to 100) | |||||||
| 2 Z-approximation | |||||||
| 3 Confidence level: 95% | |||||||
| 4 Two-sided | |||||||
| Slope of EHI and RT by field and level | ||||||||
| Compare effect estimate to zero with emmeans() | ||||||||
| field | level | ehi.trend1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|
| LVF | Local | 0.219 | 0.075 | Inf | 0.073 | 0.366 | 2.93 | .003 |
| RVF | Local | 0.096 | 0.075 | Inf | −0.05 | 0.243 | 1.288 | .198 |
| LVF | Global | 0.186 | 0.075 | Inf | 0.039 | 0.332 | 2.487 | .013 |
| RVF | Global | 0.13 | 0.075 | Inf | −0.017 | 0.276 | 1.734 | .083 |
| 1 A positive number means slower RTs for right handers, in ms per EHI unit (-100 to 100). | ||||||||
| 2 Z-approximation | ||||||||
| 3 Confidence level: 95% | ||||||||
| 4 Two-sided | ||||||||
| Estimated global bias by field, for EHI of -100 (strong left hander) | |||||
| contrast | estimate1 | SE | df | z.ratio | p.value |
|---|---|---|---|---|---|
| (LVF Local ehi-100) - (LVF Global ehi-100) | 29.412 | 3.009 | Inf | 9.776 | <.0001 |
| (RVF Local ehi-100) - (RVF Global ehi-100) | 14.59 | 3.016 | Inf | 4.837 | <.0001 |
| 1 Estimated global bias (ms) | |||||
| Estimated LVF Global Bias for EHI of -100 (strong left hander) |
| LVF_global_bias |
|---|
| 14.822 |
| Estimated global bias by field, for EHI of +100 (strong right hander) | |||||
| contrast | estimate1 | SE | df | z.ratio | p.value |
|---|---|---|---|---|---|
| LVF Local ehi100 - LVF Global ehi100 | 36.074 | 2.824 | Inf | 12.775 | <.0001 |
| RVF Local ehi100 - RVF Global ehi100 | 7.93 | 2.83 | Inf | 2.802 | .026 |
| 1 Estimated global bias (ms) | |||||
| Estimated LVF Global Bias for EHI of +100 (strong right hander) |
| LVF_global_bias |
|---|
| 28.144 |
\[
28.144 - 14.822 = 13.322ms \\
13.322/200 = 0.067ms / EHI unit
\] The model estimates that an average strong right hander (EHI
+100) will have 13.32ms more LVF global bias than a
strong left hander (EHI -100). Each unit change in EHI (-100:100)
corresponds to a 0.067ms difference in LVF global bias.
This is also the slope estimate given by the summary function:
summary(rt_model_ehi)
## Linear mixed model fit by REML ['lmerMod']
## Formula: rt ~ field:level:ehi + field:level + field:ehi + level:ehi +
## field + level + ehi + (1 | subject)
## Data: aah_for_rt_ehi_model
##
## REML criterion at convergence: 1387626.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.879612 -0.590631 -0.167132 0.363313 7.653749
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 28269.4 168.135
## Residual 42128.7 205.253
## Number of obs: 102615, groups: subject, 844
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 680.1697334 5.9429525 114.44980
## fieldRVF -2.6755865 1.8307862 -1.46144
## levelGlobal -32.7431087 1.8162558 -18.02781
## ehi 0.2190687 0.0747656 2.93007
## fieldRVF:levelGlobal 21.4828945 2.5694569 8.36087
## fieldRVF:ehi -0.1228165 0.0230212 -5.33493
## levelGlobal:ehi -0.0333102 0.0228331 -1.45886
## fieldRVF:levelGlobal:ehi 0.0666075 0.0323174 2.06104
##
## Correlation of Fixed Effects:
## (Intr) fldRVF lvlGlb ehi flRVF:G flRVF: lvlGl:
## fieldRVF -0.155
## levelGlobal -0.156 0.506
## ehi -0.064 0.010 0.010
## fldRVF:lvlG 0.110 -0.713 -0.706 -0.007
## fieldRVF:eh 0.010 -0.067 -0.033 -0.154 0.047
## levelGlbl:h 0.010 -0.033 -0.065 -0.156 0.046 0.506
## fldRVF:lvG: -0.007 0.047 0.046 0.110 -0.065 -0.712 -0.706
Test for a simple correlation between each subject’s EHI and LVF
global bias.
| Subject-level correlation: linear model | ||||
| term | estimate | std.error | statistic | p.value1 |
|---|---|---|---|---|
| (Intercept) | 16.696 | 2.454 | 6.804 | <.0001 |
| ehi | 0.042 | 0.031 | 1.374 | .17 |
| 1 Two-sided | ||||
| Subject-level correlation: Spearman's rho | ||||
| rho | statistic | p.value1 | method | alternative |
|---|---|---|---|---|
| 0.041 | 96,127,760.619 | .119 | Spearman's rank correlation rho | greater |
| 1 One-sided | ||||
In progress. Model accuracy as a binomial
effect of field, level, and EHI (continuous):
acc_ehi_model <- glmer( rt ~ field*level*ehi + (1 | subject), family = "binomial" )
| Field by level by EHI interaction (Accuracy) | |||||||
| ANOVA: compare models with vs. without interaction term | |||||||
| npar | AIC | BIC | logLik | deviance | Chisq | Df | p.value1 |
|---|---|---|---|---|---|---|---|
| 8 | 39,111.468 | 39,188.189 | −19,547.734 | 39,095.468 | - | - | - |
| 9 | 39,113.409 | 39,199.72 | −19,547.704 | 39,095.409 | 0.059 | 1 | .808 |
| 1 F-test (two-sided? https://daniellakens.blogspot.com/2016/04/one-sided-f-tests-and-halving-p-values.html) | |||||||
| Field by level interaction (acc) | ||||||||
| Compare effect estimate to zero with emmeans() | ||||||||
| field_consec | level_consec | estimate1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|
| RVF - LVF | Local - Global | 0 | 0.001 | Inf | −0.001 | 0.002 | 0.249 | .803 |
| 1 A positive number means global bias is stronger in LVF for right handers (as predicted), in logodds per EHI unit (-100 to 100). Multiply this value by 200 to get the estimated difference in LVF global bias for strong left vs. right handers. | ||||||||
| 2 Z-approximation | ||||||||
| 3 Confidence level: 95%. Lower CI for one-sided test: 0.013. | ||||||||
| 4 Two-sided | ||||||||
| Field by level interaction (acc) | |||||||
| Compare effect estimate to zero with emmeans() | |||||||
| contrast | estimate1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|
| LVF Global - LVF Local | −0.001 | 0.001 | Inf | −0.002 | 0 | −1.8 | .072 |
| RVF Global - RVF Local | −0.001 | 0.001 | Inf | −0.002 | 0 | −2.359 | .018 |
| 1 A positive number means more global bias, in logodds per EHI unit (-100 to 100) | |||||||
| 2 Z-approximation | |||||||
| 3 Confidence level: 95% | |||||||
| 4 Two-sided, uncorrected | |||||||
| Slope of EHI and acc by field and level | ||||||||
| Compare effect estimate to zero with emmeans() | ||||||||
| field | level | ehi.trend1 | SE | df2 | asymp.LCL3 | asymp.UCL3 | z.ratio | p.value4 |
|---|---|---|---|---|---|---|---|---|
| LVF | Global | −0.001 | 0.001 | Inf | −0.002 | 0.001 | −1.026 | .305 |
| RVF | Global | −0.001 | 0.001 | Inf | −0.002 | 0.001 | −0.956 | .339 |
| LVF | Local | 0 | 0.001 | Inf | −0.001 | 0.001 | 0.579 | .562 |
| RVF | Local | 0.001 | 0.001 | Inf | −0.001 | 0.002 | 1.067 | .286 |
| 1 A positive number means higher accuracy for right handers, in logodds per EHI unit (-100 to 100). | ||||||||
| 2 Z-approximation | ||||||||
| 3 Confidence level: 95% | ||||||||
| 4 Two-sided | ||||||||
Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) [glmerMod] Family: binomial ( logit ) Formula: correct ~ field * level * ehi + (1 | subject) Data: aah_for_acc_ehi_model
AIC BIC logLik deviance df.resid
39113.4 39199.7 -19547.7 39095.4 108023
Scaled residuals: Min 1Q Median 3Q Max -11.748088 0.117364 0.168282 0.238851 1.067892
Random effects: Groups Name Variance Std.Dev. subject (Intercept) 1.05841 1.02879 Number of obs: 108032, groups: subject, 844
Fixed effects: Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.9930184017 0.0532670291 74.96229 < 2e-16
fieldRVF -0.4209327473 0.0474500751 -8.87107 < 2e-16
levelLocal -0.9403339363 0.0440725615 -21.33604 < 2e-16
ehi -0.0006744722 0.0006575342 -1.02576 0.305005
fieldRVF:levelLocal 0.5311871060 0.0594032015 8.94206 < 2e-16
fieldRVF:ehi 0.0000955515 0.0005978575 0.15982
0.873020
levelLocal:ehi 0.0009994867 0.0005551631 1.80035 0.071806 .
fieldRVF:levelLocal:ehi 0.0001864551 0.0007484763 0.24911 0.803273
— Signif. codes: 0 ‘’ 0.001 ’’ 0.01 ’’ 0.05
‘.’ 0.1 ’ ’ 1
Correlation of Fixed Effects: (Intr) fldRVF lvlLcl ehi flRVF:L flRVF:
lvlLc: fieldRVF -0.528
levelLocal -0.575 0.636
ehi -0.084 0.058 0.064
fldRVF:lvlL 0.423 -0.799 -0.742 -0.046
fieldRVF:eh 0.057 -0.105 -0.069 -0.538 0.084
levelLocl:h 0.063 -0.069 -0.090 -0.583 0.066 0.635
fldRVF:lvL: -0.045 0.084 0.066 0.430 -0.081 -0.799 -0.741 optimizer
(Nelder_Mead) convergence code: 0 (OK) Model failed to converge with
max|grad| = 0.00445801 (tol = 0.002, component 1) Model is nearly
unidentifiable: very large eigenvalue - Rescale variables?
| Estimated global bias by field, for EHI of -100 (strong left hander) | ||||||
| contrast | odds.ratio1 | SE | df | null | z.ratio | p.value |
|---|---|---|---|---|---|---|
| (LVF Global ehi-100) / (LVF Local ehi-100) | 2.83 | 0.209 | Inf | 1 | 14.075 | <.0001 |
| (RVF Global ehi-100) / (RVF Local ehi-100) | 1.695 | 0.112 | Inf | 1 | 7.953 | <.0001 |
| 1 Estimated global bias. An odds ratio > 1 means global bias. | ||||||
| Estimated LVF Global Bias for EHI of -100 (strong left hander) |
| LVF_global_bias |
|---|
| 1.135 |
| Estimated global bias by field, for EHI of +100 (strong right hander) | ||||||
| contrast | odds.ratio1 | SE | df | null | z.ratio | p.value |
|---|---|---|---|---|---|---|
| LVF Global ehi100 / LVF Local ehi100 | 2.317 | 0.157 | Inf | 1 | 12.409 | <.0001 |
| RVF Global ehi100 / RVF Local ehi100 | 1.337 | 0.083 | Inf | 1 | 4.697 | <.0001 |
| 1 Estimated global bias (ms) | ||||||
| Estimated LVF Global Bias for EHI of +100 (strong right hander) |
| LVF_global_bias |
|---|
| 0.98 |
\[
log(.98) = -0.0202
log(0.135) == 0.1266
-0.0202 - 0.1266 = -0.147 (logodds)
-0.147 / 200 = -0.00007 logodds / EHI unit
\] The model estimates that an average strong left hander (EHI
-100) will have 1.135/0.98 greater relative odds of correctness for LVF
global stimuli versus a strong right hander (EHI +100). Each unit change
in EHI (-100:100) corresponds to a 0.00007 (logodds)
difference in LVF global bias. This is close to the slope estimate given
by the summary function (the difference should be due to rounding:
summary(acc_model_ehi)
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: correct ~ field * level * ehi + (1 | subject)
## Data: aah_for_acc_ehi_model
##
## AIC BIC logLik deviance df.resid
## 39113.4 39199.7 -19547.7 39095.4 108023
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -11.748088 0.117364 0.168282 0.238851 1.067892
##
## Random effects:
## Groups Name Variance Std.Dev.
## subject (Intercept) 1.05841 1.02879
## Number of obs: 108032, groups: subject, 844
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.9930184017 0.0532670291 74.96229 < 2e-16 ***
## fieldRVF -0.4209327473 0.0474500751 -8.87107 < 2e-16 ***
## levelLocal -0.9403339363 0.0440725615 -21.33604 < 2e-16 ***
## ehi -0.0006744722 0.0006575342 -1.02576 0.305005
## fieldRVF:levelLocal 0.5311871060 0.0594032015 8.94206 < 2e-16 ***
## fieldRVF:ehi 0.0000955515 0.0005978575 0.15982 0.873020
## levelLocal:ehi 0.0009994867 0.0005551631 1.80035 0.071806 .
## fieldRVF:levelLocal:ehi 0.0001864551 0.0007484763 0.24911 0.803273
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) fldRVF lvlLcl ehi flRVF:L flRVF: lvlLc:
## fieldRVF -0.528
## levelLocal -0.575 0.636
## ehi -0.084 0.058 0.064
## fldRVF:lvlL 0.423 -0.799 -0.742 -0.046
## fieldRVF:eh 0.057 -0.105 -0.069 -0.538 0.084
## levelLocl:h 0.063 -0.069 -0.090 -0.583 0.066 0.635
## fldRVF:lvL: -0.045 0.084 0.066 0.430 -0.081 -0.799 -0.741
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.00445801 (tol = 0.002, component 1)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?
Test for a simple correlation between each subject’s EHI and LVF
global bias.
| Subject-level correlation: linear model | ||||
| term | estimate | std.error | statistic | p.value1 |
|---|---|---|---|---|
| (Intercept) | 1.987 | 0.311 | 6.381 | <.0001 |
| ehi | 0.002 | 0.004 | 0.448 | .655 |
| 1 Two-sided | ||||
| Subject-level correlation: Spearman's rho | ||||
| rho | statistic | p.value1 | method | alternative |
|---|---|---|---|---|
| 0.036 | 96,571,310.453 | .147 | Spearman's rank correlation rho | greater |
| 1 One-sided | ||||